scholarly journals Compositional distinction of gut microbiota between Han Chinese and Tibetan populations with liver cirrhosis

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12142
Author(s):  
Hui Huan ◽  
Tao Ren ◽  
Li Xu ◽  
Hong Hu ◽  
Chao Liu
Keyword(s):  
Liver Cirrhosis ◽  
Gut Microbiota ◽  
Healthy Volunteers ◽  
16S Rrna Gene Sequencing ◽  
Han Chinese ◽  
Chinese Patients ◽  
Rrna Gene ◽  
Chinese Populations ◽  
Intestinal Bacterial Community ◽  
Relative Abundances

Background Liver cirrhosis (LC) is caused by numerous chronic liver diseases and its complications are associated with qualitative and quantitative alterations of the gut microbiota. Previous studies have revealed the characteristics of gut microbiota in Han Chinese patients with LC and different compositions of gut microbiota were reported between the Tibetan and Han Chinese populations. This study was designed to evaluate the unique features of the gut microbiota of Tibetans and compare the differences of gut microbiota between Tibetan and Han Chinese patients with LC. Methods Thirty-six patients with liver cirrhosis and nineteen healthy volunteers, from both Tibetan and Han Chinese populations, were enrolled and fecal samples were collected for 16S rRNA gene sequencing analyses. Results Significant differences were found in the gut microbiota of healthy volunteers and between Tibetan and Han Chinese patients with LC. In the Han Chinese patients with cirrhosis (HLC) group the relative abundances of the phylum Bacteroidetes was significantly reduced (P < 0.001), whereas in the Tibetan patients with cirrhosis (TLC) group Firmicutes and Actinobacteria were highly enriched (P = 0.01 and 0.03, respectively). At the genus level, the relative abundances of Anaerostipes (P < 0.001), Bifidobacterium (P = 0.03), and Blautia (P = 0.004) were prevalent, while Alloprevotella, Dorea, Prevotella_2, Prevotella_7 and Prevotella_9 were decreased in the TLC group compared to the HLC group (P < 0.01). Conclusion Our findings showed how the intestinal bacterial community shifted in Tibetan patients with cirrhosis.

scholarly journals Changes in gut microbiota composition and their associations with cortisol, melatonin and interleukin 6 in patients with chronic insomnia

2021 ◽  
Author(s):  
AA Masyutina ◽  
LN Gumenyuk ◽  
YuV Fatovenko ◽  
LE Sorokina ◽  
SS Bayramova ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Sleep Quality ◽  
Healthy Volunteers ◽  
16S Rrna Gene Sequencing ◽  
Cross Sectional Study ◽  
Taxonomic Composition ◽  
Chronic Insomnia ◽  
Control Group ◽  
Rrna Gene ◽  
Cross Sectional

The relationship between the gut microbiota and chronic insomnia remains understudied. The aim of this paper was to investigate changes in the taxonomic composition of the gut microbiota and their associations with the levels of cortisol, melatonin and IL6 in patients with chronic insomnia. Our comparative prospective cross-sectional study enrolled 55 patients with chronic insomnia, who formed the main group (female patients: 58.2%, male patients: 41.8%; mean age 31.6 ± 7.4 years), and 50 healthy volunteers, who comprised the control group (females: 68.0%, males: 32.0%; mean age 33.2 ± 6.6 years). The taxonomic composition of the gut microbiota was profiled using 16S rRNA gene sequencing. Plasma cortisol and IL 6 and urine melatonin were measured by means of ELISA. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI). In patients with chronic insomnia, the abundance of Faecalibacterium (p = 0.048), Prevotella 9 (p < 0.001) and Lachnospira (p = 0.036) was lower, whereas the abundance of Blautia (p = 0.012) and Eubacteriumhallii (p = 0.003) was higher than in healthy volunteers. Significant correlations were established between the levels of IL6 and the abundance of Faecalibacterium (r = –0.44; p = 0.001) and Blautia (r = 0.42; p < 0.001), as well as between cortisol concentrations and the abundance of Lachnospira (r = –0.41; p = 0.048). The abundance of Faecalibacterium and Blautiaс was correlated with higher PSQI (r = –0.47, p = 0.001; r = 0.45, p < 0.001, respectively). Our study contributed to the pool of data about changes in the gut microbiota and their associations with some endocrine and inflammation markers in patients with chronic insomnia. These data can be exploited to propose new strategies for the diagnosis and personalized treatment of insomnia aimed at normalizing the patient’s gut microbiota.

scholarly journals Bioconversion Variation of Ginsenoside CK Mediated by Human Gut Microbiota From Healthy Volunteers and Colorectal Cancer Patients

2021 ◽  
Author(s):  
Yin-Ping Guo ◽  
Li Shao ◽  
Li Wang ◽  
Man-Yun Chen ◽  
Wei Zhang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
16S Rrna ◽  
Gut Microbiota ◽  
Healthy Volunteers ◽  
Healthy Subjects ◽  
Positive Association ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Significant Difference

Abstract Background: Ginsenoside CK (GCK) serves as the potential anti-colorectal cancer (CRC) protopanaxadiol (PPD)-type saponin, which could be mainly bio-converted to yield PPD by gut microbiota. Meanwhile, the anti-CRC effects of GCK could be altered by gut microbiota due to its different diversity in CRC patients. We aimed to investigate the bioconversion variation of GCK mediated by gut microbiota from CRC patients by comparing with healthy subjects.Methods: Gut microbiota profiled by 16S rRNA gene sequencing was collected from healthy volunteers and CRC patients. GCK was incubated with gut microbiota in vitro. A LC-MS/MS method was validated to quantify GCK and PPD after incubation at different time points.Results: The bioconversion of GCK in healthy subjects group was much faster than CRC group, as well as the yield of PPD. Moreover, significant difference of PPD concentration between healthy subjects group and CRC group could be observed at 12 h, 48 h and 72 h check points. According to 16S rRNA sequencing, the profiles of gut microbiota derived from healthy volunteers and CRC patients significantly varied, in which 12 differentially abundant taxon were found, such as Bifidobacterium, Roseburia, Bacteroides and Collinsella. Spearman’s correlation analysis showed bacteria enriched in healthy subjects group were positively associated with biotransformation of GCK, while bacteria enriched in CRC group displayed non correlation characters. Among them, Roseburia which could secrete β-glycosidase showed the strongest positive association with the bioconversion of GCK.Conclusion: The bioconversion of GCK in healthy subjects was much faster than CRC patients mediated by gut microbiota, which might alter the anti-CRC effects of GCK.

scholarly journals Specific Gut Microbiome and Serum Metabolome Changes in Lung Cancer Patients

2021 ◽  
Vol 11 ◽  
Author(s):  
Feng Zhao ◽  
Rui An ◽  
Liqian Wang ◽  
Jikang Shan ◽  
Xianjun Wang
Keyword(s):  
Lung Cancer ◽  
Gut Microbiota ◽  
Healthy Volunteers ◽  
Gut Microbiome ◽  
16S Rrna Gene Sequencing ◽  
Serum Levels ◽  
Rrna Gene ◽  
Serum Samples ◽  
Combined Analysis ◽  
Serum Metabolites

BackgroundLung cancer (LC) is one of the most aggressive, prevalent and fatal malignancies. Gut microbes and their associated metabolites are thought to cause and modulate LC development, albeit influenced by the host genetic make-up and environment. Herein, we identified and classified gut microbiota and serum metabolites associated with LC.MethodsStool samples were collected from 41 LC patients and 40 healthy volunteers. The gut microbiota was analyzed using 16S rRNA gene sequencing. Serum samples were collected from the same LC patients (n=30) and healthy volunteers (n=30) and serum metabolites were analyzed using liquid chromatography-mass spectrometry (LC-MS). Microbiome and metabolome data were analyzed separately and integrated for combined analysis using various bioinformatics methods.ResultsSerum metabolomics uncovered 870 metabolites regulated in 76 metabolic pathways in both groups. Microbial diversity analyses identified 15967 operational taxonomic units (OTUs) in groups. Of these, the abundance of 232 OTUs was significantly different between HC and LC groups. Also, serum levels of glycerophospholipids (LysoPE 18:3, LysoPC 14:0, LysoPC 18:3), Imidazopyrimidines (Hypoxanthine), AcylGlcADG 66:18; AcylGlcADG (22:6/22:6/22:6) and Acylcarnitine 11:0 were substantially different between HC and LC groups. Combined analysis correlated LC-associated microbes with metabolites, such as Erysipelotrichaceae_UCG_003, Clostridium and Synergistes with glycerophospholipids.ConclusionsThere is an intricate relationship between gut microbiome and levels of several metabolites such as glycerophospholipids and imidazopyrimidines. Microbial-associated metabolites are potential diagnostic biomarkers and therapeutic targets for LC.

scholarly journals Gut microbiota signatures in Schistosoma japonicum infection-induced liver cirrhosis patients: a case–control study

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Qi-Feng Gui ◽  
Hui-Lin Jin ◽  
Feng Zhu ◽  
Hai-Feng Lu ◽  
Qin Zhang ◽  
...  
Keyword(s):  
Liver Cirrhosis ◽  
Gut Microbiota ◽  
Schistosoma Japonicum ◽  
Alpha Diversity ◽  
16S Rrna Gene Sequencing ◽  
Illumina Miseq ◽  
Control Group ◽  
Rrna Gene ◽  
Healthy Individuals ◽  
Rrna Gene Sequencing

Abstract Background Several studies have assessed the role of gut microbiota in various cirrhosis etiologies, however, none has done so in the context of Schistosoma japonicum infection in humans. We, therefore, sought to determine whether gut microbiota is associated with S. japonicum infection-induced liver cirrhosis. Methods From December 2017 to November 2019, 24 patients with S. japonicum infection-induced liver cirrhosis, as well as 25 age- and sex-matched controls from the Zhejiang Province, China, were enrolled. Fecal samples were collected and used for 16S rRNA gene sequencing (particularly, the hypervariable V4 region) using the Illumina MiSeq system. Wilcoxon Rank-Sum and PERMANOVA tests were used for analysis. Results Eight hundred and seven operational taxonomic units (OTUs) were detected, of which, 491 were common between the two groups, whereas 123 and 193 were unique to the control and cirrhosis groups, respectively. Observed species, Chao, ACE, Shannon, Simpson, and Good’s coverage indexes, used for alpha diversity analysis, showed values of 173.4 ± 63.8, 197.7 ± 73.0, 196.3 ± 68.9, 2.96 ± 0.57, 0.13 ± 0.09, and 1.00 ± 0.00, respectively, in the control group and 154.0 ± 68.1, 178.6 ± 75.1, 179.9 ± 72.4, 2.68 ± 0.76, 0.19 ± 0.18, and 1.00 ± 0.00, respectively, in the cirrhosis group, with no significant differences observed between the groups. Beta diversity was evaluated by weighted UniFrac distances, with values of 0.40 ± 0.13 and 0.40 ± 0.11 in the control and cirrhosis groups, respectively (P > 0.05). PCA data also confirmed this similarity (P > 0.05). Meanwhile, the relative abundance of species belonging to the Bacilli class was higher in cirrhosis patients [median: 2.74%, interquartile range (IQR): 0.18–7.81%] than healthy individuals (median: 0.15%, IQR: 0.47–0.73%; P < 0.01), and that of Lactobacillales order was also higher in cirrhosis patients (median: 2.73%, IQR: 0.16–7.80%) than in healthy individuals (median: 0.12%, IQR: 0.03–0.70%; P < 0.05). Conclusions Cumulatively, our results suggest that the gut microbiota of S. japonicum infection-induced liver cirrhosis patients is similar to that of healthy individuals, indicating that bacterial taxa cannot be used as non-invasive biomarkers for S. japonicum infection-induced liver cirrhosis.

scholarly journals Gut Microbiota Profiles Differ among Individuals Depending on Their Region of Origin: An Italian Pilot Study

2019 ◽  
Vol 16 (21) ◽  
pp. 4065 ◽  
Author(s):  
Fontana ◽  
Panebianco ◽  
Picchianti-Diamanti ◽  
Laganà ◽  
Cavalieri ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Healthy Volunteers ◽  
Dietary Habits ◽  
16S Rrna Gene Sequencing ◽  
Shannon Index ◽  
Rrna Gene ◽  
Microbiota Composition ◽  
Region Of Origin ◽  
Age Classes ◽  
Italian Regions

Background and aims: Microbiota heterogeneity among humans is mainly due to genetic background, age, dietary habits, lifestyle and local environments. In this study we investigated whether the gut microbiota profile of Italian healthy volunteers could differ based on their geographical origin. Materials and Methods: 16S rRNA gene sequencing was employed to analyze the gut microbiota of 31 healthy volunteers from three different Italian regions: Apulia (South), Lazio (Center) and Lombardy (North). Results: Differences in microbiota composition were detected when the study participants were grouped by their region of origin and when they were classified based on age classes (p-values < 0.05). Also species richness was significantly different both according to Italian Regions (median richness: 177.8 vs. 140.7 vs. 168.0 in Apulia, Lazio and Lombardy; p < 0.001) and according to age classes (median richness: 140.1 vs. 177.8 vs. 160.0 in subjects < 32, 32–41 and > 41 years; p < 0.001), whereas the Shannon index and beta diversity did not change. Conclusions: This study identified differences in the gut microbiota composition and richness among individuals with the same ethnicity coming from three different Italian regions. Our results underline the importance of studies on population-specific variations in human microbiota composition leading to geographically tailored approaches to microbiota engineering.

scholarly journals Bioconversion variation of ginsenoside CK mediated by human gut microbiota from healthy volunteers and colorectal cancer patients

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Yin-Ping Guo ◽  
Li Shao ◽  
Li Wang ◽  
Man-Yun Chen ◽  
Wei Zhang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
16S Rrna ◽  
Gut Microbiota ◽  
Healthy Volunteers ◽  
Healthy Subjects ◽  
Positive Association ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Colorectal Cancer Patients

Abstract Background Ginsenoside CK (GCK) serves as the potential anti-colorectal cancer (CRC) protopanaxadiol (PPD)-type saponin, which could be mainly bio-converted to yield PPD by gut microbiota. Meanwhile, the anti-CRC effects of GCK could be altered by gut microbiota due to their different diversity in CRC patients. We aimed to investigate the bioconversion variation of GCK mediated by gut microbiota from CRC patients by comparing with healthy subjects. Methods Gut microbiota profiled by 16S rRNA gene sequencing were collected from healthy volunteers and CRC patients. GCK was incubated with gut microbiota in vitro. A LC-MS/MS method was validated to quantify GCK and PPD after incubation at different time points. Results The bioconversion of GCK in healthy subjects group was much faster than CRC group, as well as the yield of PPD. Moreover, significant differences of PPD concentration between healthy subjects group and CRC group could be observed at 12 h, 48 h and 72 h check points. According to 16S rRNA sequencing, the profiles of gut microbiota derived from healthy volunteers and CRC patients significantly varied, in which 12 differentially abundant taxon were found, such as Bifidobacterium, Roseburia, Bacteroides and Collinsella. Spearman’s correlation analysis showed bacteria enriched in healthy subjects group were positively associated with the biotransformation of GCK, while bacteria enriched in CRC group displayed non correlation character. Among them, Roseburia which could secrete β-glycosidase showed the strongest positive association with the bioconversion of GCK. Conclusions The bioconversion of GCK in healthy subjects was much faster than CRC patients mediated by gut microbiota, which might alter the anti-CRC effects of GCK.

scholarly journals Diversity, Composition and Functional Inference of Gut Microbiota in Indian Cabbage white Pieris canidia (Lepidoptera: Pieridae)

Life ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 254
Author(s):  
Ying Wang ◽  
Jianqing Zhu ◽  
Jie Fang ◽  
Li Shen ◽  
Shuojia Ma ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
16S Rrna Gene Sequencing ◽  
Adult Survival ◽  
Rrna Gene ◽  
Life Stages ◽  
Microbial Composition ◽  
Significant Difference ◽  
Functional Inference ◽  
Rrna Gene Sequencing ◽  
Insect Fitness

We characterized the gut microbial composition and relative abundance of gut bacteria in the larvae and adults of Pieris canidia by 16S rRNA gene sequencing. The gut microbiota structure was similar across the life stages and sexes. The comparative functional analysis on P. canidia bacterial communities with PICRUSt showed the enrichment of several pathways including those for energy metabolism, immune system, digestive system, xenobiotics biodegradation, transport, cell growth and death. The parameters often used as a proxy of insect fitness (development time, pupation rate, emergence rate, adult survival rate and weight of 5th instars larvae) showed a significant difference between treatment group and untreated group and point to potential fitness advantages with the gut microbiomes in P. canidia. These data provide an overall view of the bacterial community across the life stages and sexes in P. canidia.

scholarly journals Gut microbiota markers associated with obesity and overweight in Italian adults

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Vanessa Palmas ◽  
Silvia Pisanu ◽  
Veronica Madau ◽  
Emanuela Casula ◽  
Andrea Deledda ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Relative Abundance ◽  
Smoking Status ◽  
16S Rrna Gene Sequencing ◽  
Normal Weight ◽  
Activity Level ◽  
Rrna Gene ◽  
Illumina Platform ◽  
Obesity And Overweight ◽  
Rrna Gene Sequencing

AbstractIn the present study, we characterized the distinctive signatures of the gut microbiota (GM) from overweight/obese patients (OB), and normal-weight controls (NW), both of Sardinian origin. Fecal bacterial composition of 46 OB patients (BMI = 36.6 ± 6.0; F/M = 40/6) was analyzed and compared to that of 46 NW subjects (BMI = 21.6 ± 2.1; F/M = 41/5), matched for sex, age and smoking status, by using 16S rRNA gene sequencing on MiSeq Illumina platform. The gut microbial community of OB patients exhibited a significant decrease in the relative abundance of several Bacteroidetes taxa (i.e. Flavobacteriaceae, Porphyromonadaceae, Sphingobacteriaceae, Flavobacterium, Rikenella spp., Pedobacter spp., Parabacteroides spp., Bacteroides spp.) when compared to NW; instead, several Firmicutes taxa were significantly increased in the same subjects (Lachnospiraceae, Gemellaceae, Paenibacillaceae, Streptococcaceae, Thermicanaceae, Gemella, Mitsuokella, Streptococcus, Acidaminococcus spp., Eubacterium spp., Ruminococcus spp., Megamonas spp., Streptococcus, Thermicanus, Megasphaera spp. and Veillonella spp.). Correlation analysis indicated that body fatness and waist circumference negatively correlated with Bacteroidetes taxa, while Firmicutes taxa positively correlated with body fat and negatively with muscle mass and/or physical activity level. Furthermore, the relative abundance of several bacterial taxa belonging to Enterobacteriaceae family, known to exhibit endotoxic activity, was increased in the OB group compared to NW. The results extend our knowledge on the GM profiles in Italian OB, identifying novel taxa linking obesity and intestine.

scholarly journals Gut microbiota accelerates cisplatin-induced acute liver injury associated with robust inflammation and oxidative stress in mice

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Shenhai Gong ◽  
Yinglin Feng ◽  
Yunong Zeng ◽  
Huanrui Zhang ◽  
Meiping Pan ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
16S Rrna ◽  
Gut Microbiota ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Metabolomic Analysis ◽  
Rrna Gene Sequencing ◽  
And Oxidative Stress

Abstract Background Gut microbiota has been reported to be disrupted by cisplatin, as well as to modulate chemotherapy toxicity. However, the precise role of intestinal microbiota in the pathogenesis of cisplatin hepatotoxicity remains unknown. Methods We compared the composition and function of gut microbiota between mice treated with and without cisplatin using 16S rRNA gene sequencing and via metabolomic analysis. For understanding the causative relationship between gut dysbiosis and cisplatin hepatotoxicity, antibiotics were administered to deplete gut microbiota and faecal microbiota transplantation (FMT) was performed before cisplatin treatment. Results 16S rRNA gene sequencing and metabolomic analysis showed that cisplatin administration caused gut microbiota dysbiosis in mice. Gut microbiota ablation by antibiotic exposure protected against the hepatotoxicity induced by cisplatin. Interestingly, mice treated with antibiotics dampened the mitogen-activated protein kinase pathway activation and promoted nuclear factor erythroid 2-related factor 2 nuclear translocation, resulting in decreased levels of both inflammation and oxidative stress in the liver. FMT also confirmed the role of microbiota in individual susceptibility to cisplatin-induced hepatotoxicity. Conclusions This study elucidated the mechanism by which gut microbiota mediates cisplatin hepatotoxicity through enhanced inflammatory response and oxidative stress. This knowledge may help develop novel therapeutic approaches that involve targeting the composition and metabolites of microbiota.

scholarly journals Comparison between 16S rRNA and shotgun sequencing data for the taxonomic characterization of the gut microbiota

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Francesco Durazzi ◽  
Claudia Sala ◽  
Gastone Castellani ◽  
Gerardo Manfreda ◽  
Daniel Remondini ◽  
...  
Keyword(s):  
16S Rrna ◽  
Gut Microbiota ◽  
16S Rrna Gene ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Shotgun Sequencing ◽  
Rrna Gene ◽  
Metagenomic Sequencing ◽  
Experimental Conditions ◽  
Rrna Gene Sequencing

AbstractIn this paper we compared taxonomic results obtained by metataxonomics (16S rRNA gene sequencing) and metagenomics (whole shotgun metagenomic sequencing) to investigate their reliability for bacteria profiling, studying the chicken gut as a model system. The experimental conditions included two compartments of gastrointestinal tracts and two sampling times. We compared the relative abundance distributions obtained with the two sequencing strategies and then tested their capability to distinguish the experimental conditions. The results showed that 16S rRNA gene sequencing detects only part of the gut microbiota community revealed by shotgun sequencing. Specifically, when a sufficient number of reads is available, Shotgun sequencing has more power to identify less abundant taxa than 16S sequencing. Finally, we showed that the less abundant genera detected only by shotgun sequencing are biologically meaningful, being able to discriminate between the experimental conditions as much as the more abundant genera detected by both sequencing strategies.

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